Information screen projection method and device for intelligent riding glasses

Abstract

The invention relates to the technical field of intelligent riding glasses, and discloses an information screen projection method and device for intelligent riding glasses, and the method comprises the steps: collecting a riding environment feature data set in a riding process, and generating a riding vibration compensation parameter set and an ambient light adaptation parameter set according to the riding environment feature data set; performing optical waveguide coupling on the intelligent riding glasses to obtain a dynamic diffraction angle adjustment parameter set; according to the dynamic diffraction angle adjustment parameter set, performing adaptive modulation on an electric control liquid crystal layer and a nano surface grating in the optical waveguide to obtain an optical waveguide coupling efficiency optimization result; the backlight power and display image parameters are cooperatively adjusted based on the optical waveguide coupling efficiency optimization result, and an intelligent screen projection display result is output, the problem that display lags when the ambient light rapidly changes is effectively solved, real-time adjustment of the optical characteristics of the optical waveguide is achieved, and consistency and stability of screen projection display quality are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of smart cycling glasses, and in particular to an information projection method and device for smart cycling glasses. Background Art

[0002] Smart cycling glasses exhibit unstable display quality in complex riding environments. Traditional AR glasses' optical waveguide systems primarily utilize fixed diffraction gratings and static angle-of-incidence control. While capable of basic image projection in laboratory environments, their optical transmission efficiency is generally low, reaching only approximately 1% light utilization, making it difficult to meet the display brightness requirements in strong outdoor light conditions. Furthermore, multi-dimensional vibration interference generated during cycling can cause optical path deviation and display jitter, while rapidly changing ambient light conditions can severely impact the visibility and contrast of displayed content. Summary of the Invention

[0003] The present invention provides an information projection method and device for smart cycling glasses. The present invention effectively solves the problem of display lag when the ambient light changes rapidly, realizes real-time adjustment of the optical properties of the optical waveguide, and ensures the consistency and stability of the projection display quality.

[0004] A first aspect of the present invention provides an information projection method for smart cycling glasses, the information projection method for smart cycling glasses comprising: Collecting a riding environment feature data set during riding, and generating a riding vibration compensation parameter set and an ambient light adaptation parameter set based on the riding environment feature data set; Performing optical waveguide coupling on the smart cycling glasses according to the cycling vibration compensation parameter set and the ambient light adaptation parameter set to obtain a dynamic diffraction angle adjustment parameter set; Adaptively modulating the electrically controlled liquid crystal layer and the nano-surface grating in the optical waveguide according to the dynamic diffraction angle adjustment parameter set to obtain an optical waveguide coupling efficiency optimization result; Based on the optical waveguide coupling efficiency optimization result, the backlight power and display image parameters are coordinated to output the intelligent projection display result.

[0005] In combination with the first aspect, in a first implementation of the first aspect of the present invention, collecting a riding environment feature dataset during riding, and generating a riding vibration compensation parameter set and an ambient light adaptation parameter set based on the riding environment feature dataset, includes: Sampling the data using a three-axis acceleration sensor and a three-axis gyroscope sensor to obtain a raw riding vibration data stream, and performing bandpass filtering and feature extraction on the raw riding vibration data stream to obtain a vibration signal component; The ambient light intensity sensor is used to detect light intensity and extract features to obtain the ambient light intensity component; Integrating the vibration signal component and the ambient light intensity component to obtain a riding environment feature dataset; Performing frequency domain decomposition and harmonic analysis on the vibration signal components in the riding environment characteristic data set to obtain a riding vibration compensation parameter set; A prediction is performed based on the ambient light intensity component in the riding environment feature data set to obtain an ambient light adaptation parameter set.

[0006] In combination with the first aspect, in a second implementation of the first aspect of the present invention, performing frequency domain decomposition and harmonic analysis on the vibration signal components in the riding environment feature dataset to obtain a riding vibration compensation parameter set includes: Using a Fourier transform algorithm, performing frequency domain conversion on the vibration signal components in the riding environment characteristic dataset to obtain a frequency domain vibration dataset; Extracting harmonic components from the frequency domain vibration data set to obtain a target frequency component data set, and performing third harmonic vibration compensation based on the target frequency component data set to obtain a vibration model parameter set; The three-dimensional optical path offset is calculated according to the vibration model parameter group to obtain a riding vibration compensation parameter set.

[0007] In combination with the first aspect, in a third implementation of the first aspect of the present invention, the step of performing prediction based on the ambient light intensity component in the riding environment feature dataset to obtain the ambient light adaptation parameter set includes: Performing time series processing on the ambient light intensity component in the riding environment feature data set to obtain a light intensity data sequence; Inputting the light intensity data sequence into a long short-term memory network for light intensity prediction to obtain predicted light intensity data, wherein the long short-term memory network includes a first long short-term memory layer, a second long short-term memory layer, and a fully connected layer, wherein the first long short-term memory layer includes 64 long short-term memory units, the second long short-term memory layer includes 128 long short-term memory units, and the fully connected layer uses a ReLU activation function; Optical parameter mapping is performed based on the predicted light intensity data to obtain an optical parameter mapping result, and parameter adaptation is performed according to the optical parameter mapping result and the ambient light intensity change rate to obtain the ambient light adaptation parameter set.

[0008] In combination with the first aspect, in a fourth implementation of the first aspect of the present invention, performing optical waveguide coupling on the smart cycling glasses according to the cycling vibration compensation parameter set and the ambient light adaptation parameter set to obtain a dynamic diffraction angle adjustment parameter set includes: Performing a weighted calculation of frequency domain components based on the riding vibration compensation parameter set to obtain a vibration compensation angle component; Perform optical parameter mapping calculation according to the ambient light adaptation parameter set to obtain an ambient light adaptation angle component; Combined with riding posture data, the head pitch angle and roll angle of the smart riding glasses are weightedly fused to obtain the posture compensation angle component; The vibration compensation angle component, the ambient light adaptation angle component, and the posture compensation angle component are optically waveguide coupled to obtain a dynamic diffraction angle adjustment parameter set.

[0009] In combination with the first aspect, in a fifth implementation of the first aspect of the present invention, performing optical waveguide coupling on the vibration compensation angle component, the ambient light adaptation angle component, and the posture compensation angle component to obtain a dynamic diffraction angle adjustment parameter set includes: Performing optical waveguide geometric factor correction on the vibration compensation angle component to obtain a vibration angle parameter after geometric correction; Reconstructing the sinusoidal wave of the frequency domain component based on the vibration angle parameter after the geometric correction to obtain a reconstructed vibration compensation angle value; performing differential weighted calculation of the pitch angle and the roll angle based on the attitude compensation angle component to obtain a weighted attitude compensation angle value; A weighted coefficient matrix is ​​established according to the reconstructed vibration compensation angle value, the ambient light adaptation angle component and the weighted posture compensation angle value, and a linear combination is performed based on the weighted coefficient matrix to obtain a dynamic diffraction angle adjustment parameter set.

[0010] In combination with the first aspect, in a sixth implementation of the first aspect of the present invention, adaptively modulating the electrically controlled liquid crystal layer and the nano-surface grating in the optical waveguide according to the dynamic diffraction angle adjustment parameter set to obtain an optical waveguide coupling efficiency optimization result includes: Performing voltage control mapping based on the dynamic diffraction angle adjustment parameter set to obtain liquid crystal layer voltage modulation parameters and grating voltage modulation parameters; performing electric field modulation on the electrically controlled liquid crystal layer to orient nematic liquid crystal molecules according to the liquid crystal layer voltage modulation parameter, thereby obtaining a result of adjusting the refractive index distribution of the liquid crystal layer; Dynamically adjusting the effective refractive index difference of the nano-surface grating based on the grating voltage modulation parameter to obtain a grating diffraction efficiency adjustment result; The adjustment result of the refractive index distribution of the liquid crystal layer and the adjustment result of the grating diffraction efficiency are input into a photodetector to monitor the light intensity, and the optimization result of the optical waveguide coupling efficiency is obtained.

[0011] In combination with the first aspect, in a seventh implementation of the first aspect of the present invention, performing voltage control mapping based on the dynamic diffraction angle adjustment parameter set to obtain liquid crystal layer voltage modulation parameters and grating voltage modulation parameters includes: Calculating the reference angle difference and angle change rate of the dynamic diffraction angle adjustment parameter set to obtain an angle offset and angle change speed parameter set; Performing liquid crystal molecule orientation angle mapping based on the angle offset to obtain a target liquid crystal orientation angle value, and performing electric field intensity conversion according to the target liquid crystal orientation angle value to obtain a liquid crystal layer voltage modulation parameter; Grating effective refractive index difference mapping is performed according to the angle offset and the angle change speed parameter group to obtain a target refractive index difference value, and surface relief grating voltage conversion is performed based on the target refractive index difference value to obtain a grating voltage modulation parameter.

[0012] In combination with the first aspect, in an eighth implementation of the first aspect of the present invention, the backlight power and display image parameters are collaboratively adjusted based on the optical waveguide coupling efficiency optimization result, and the smart projection display result is output, including: Calculating a ratio of a target coupling efficiency to a current coupling efficiency based on the optical waveguide coupling efficiency optimization result to obtain a power compensation coefficient, and calculating a backlight power gain based on the power compensation coefficient and ambient light intensity to obtain a dynamic backlight power value; Performing brightness linearity analysis and color temperature offset prediction on the dynamic backlight power value to obtain a parameter group of the impact of power change on image display, and performing image contrast inverse compensation and color saturation inverse compensation based on the influencing parameter group to obtain a collaborative image parameter adjustment value; Inputting the dynamic backlight power value and the collaborative image parameter adjustment value into a display driving algorithm to perform power and image joint optimization to obtain a collaboratively adjusted driving parameter group; Real-time display quality monitoring and dynamic feedback correction are performed based on the collaboratively adjusted driving parameter group, and the intelligent projection display result is output.

[0013] A second aspect of the present invention provides an information projection device for smart cycling glasses, the information projection device for smart cycling glasses comprising: An acquisition module is used to collect a riding environment feature data set during riding, and generate a riding vibration compensation parameter set and an ambient light adaptation parameter set according to the riding environment feature data set; an optical waveguide coupling module, configured to perform optical waveguide coupling on the smart cycling glasses according to the cycling vibration compensation parameter set and the ambient light adaptation parameter set, to obtain a dynamic diffraction angle adjustment parameter set; An adaptive modulation module, configured to adaptively modulate the electrically controlled liquid crystal layer and the nano-surface grating in the optical waveguide according to the dynamic diffraction angle adjustment parameter set, to obtain an optical waveguide coupling efficiency optimization result; A collaborative adjustment module is used to collaboratively adjust the backlight power and display image parameters based on the optical waveguide coupling efficiency optimization result, and output the intelligent projection display result. Compared with the prior art, the present invention has the following beneficial effects: by integrating a three-axis acceleration sensor, a three-axis gyroscope sensor, and an ambient light intensity sensor, an all-round perception system for the riding environment is established. Compared with the single sensor solution of the prior art, it can simultaneously capture the multi-dimensional environmental characteristics of vibration, posture, and illumination. By using the Fourier transform algorithm and the third harmonic vibration compensation model, the frequency domain characteristics of the riding vibration can be accurately analyzed and targeted compensation can be performed. Compared with the traditional time-domain linear compensation method, the interference effect of vibration on the optical path is significantly suppressed, ensuring the stability of the displayed image. By constructing a double-layer LSTM network architecture for ambient light intensity prediction, compared with the passive light intensity adaptation method of the prior art, active prediction and advance adjustment are achieved, effectively solving the problem of display lag when the ambient light changes rapidly, and improving the environmental adaptability of the display system. A three-dimensional coupling optimization algorithm for vibration compensation, ambient light adaptation, and riding posture is established. Through the linear combination processing of the weighted coefficient matrix, compared with the single parameter adjustment of the prior art, multi-factor collaborative optimization is achieved, significantly improving the coupling efficiency of the optical waveguide. Through electric field modulation of nematic liquid crystal molecular orientation and dynamic adjustment of the effective refractive index difference of nano-surface grating, real-time adjustment of the optical properties of the optical waveguide is achieved compared to the traditional fixed optical structure, and a power-image joint optimization mechanism is established. Through brightness linearity analysis and reverse compensation algorithm, compared with the independent parameter adjustment method of the existing technology, the coordinated optimization of backlight power and image parameters is achieved, ensuring the consistency and stability of display quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] The structures, proportions, sizes, etc. depicted in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not intended to limit the conditions under which the present invention can be implemented and therefore have no substantive technical significance. Any structural modifications, changes in proportional relationships, or adjustments in size should still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and objectives that can be achieved by the present invention.

[0016] Figure 1 This is a flow chart of an information projection method for smart cycling glasses provided by an embodiment of the present invention; Figure 2 It is a schematic block diagram of the structure of the information projection device of the smart cycling glasses provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0019] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in the specification and appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0020] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations. Figure 1 An embodiment of the information projection method of the smart cycling glasses in the embodiment of the present invention includes: Step 100: Collect a riding environment feature data set during riding, and generate a riding vibration compensation parameter set and an ambient light adaptation parameter set based on the riding environment feature data set; It is understood that the execution subject of the present invention can be the information projection device of the smart cycling glasses, or it can be a terminal or a server, and the specific details are not limited here. The embodiment of the present invention is described by taking the server as the execution subject as an example.

[0021] Specifically, a triaxial accelerometer and triaxial gyroscope sensor, housed within the frames of the smart cycling glasses, synchronously acquire linear acceleration and angular velocity components at a sampling frequency of 1000Hz, forming a raw cycling vibration data stream. This data is then cleaned using front-end hardware-level bandpass filtering, with a low-frequency cutoff of 0.5Hz to eliminate gravity drift and a high-frequency cutoff of 50Hz to remove electromagnetic interference or high-frequency mechanical noise, thereby retaining the effective vibration components. Key features such as the dominant frequency component, instantaneous acceleration peak, and periodic oscillation amplitude are extracted from the filtered signal to form the vibration signal component for dynamic modeling. Simultaneously, an ambient light intensity sensor integrated on the outside of the glasses lens collects light in real time, with a response time optimized to less than 10ms and a measurement range ranging from 0.1 lux of dim light to 100,000 lux of direct sunlight. The collected raw light intensity data is low-pass filtered to remove high-frequency flicker interference, and then the current light amplitude, rate of change, and short-term gradient are extracted to obtain the ambient light intensity component. The vibration signal components and ambient light intensity components are timestamp aligned and vector-level integrated to construct a unified riding environment feature dataset, where each component represents three-axis acceleration, three-axis angular velocity, and current ambient light intensity. A fast Fourier transform is performed on the vibration signal components in the riding environment feature dataset to extract the main frequency structure in the range of 1Hz to 20Hz, and it is fitted and reconstructed in combination with the third-order harmonic model to obtain a dynamic compensation parameter group including amplitude, fundamental frequency, and phase, which is used to characterize the optical path perturbation trend and output the optical path correction angle. The ambient light intensity component in the riding environment feature dataset is input into a time series prediction model based on the long short-term memory network architecture. The illumination change value for the next 500ms is predicted by learning the illumination trend of multiple historical time segments. The prediction results are mapped to specific optical waveguide coupling adjustment angles to obtain the ambient light adaptation parameter set.

[0022] Step 200: Perform optical waveguide coupling on the smart cycling glasses according to the cycling vibration compensation parameter set and the ambient light adaptation parameter set to obtain a dynamic diffraction angle adjustment parameter set; Specifically, based on the riding vibration compensation parameter set, the amplitude and phase information of each harmonic component is extracted and input into a frequency domain superposition model for weighted calculation. This frequency domain model retains the fundamental frequency structure while adding second and third harmonics to improve the description of nonlinear vibration behavior. Vibration signals are synthesized into stable angular offsets through Fourier reconstruction to obtain the vibration compensation angle component. Based on the illumination prediction results in the ambient light adaptation parameter set, the light intensity is mapped to the optical diffraction angle offset to obtain the ambient light adaptation angle component. This mapping is set according to an empirical response curve. For example, when the light intensity is below 1000 lux, the high-gain optical state is enabled. If the light intensity is in the medium range, the default angle is maintained. Under conditions of strong light exceeding 50,000 lux, the anti-glare angle offset mechanism is activated. At the same time, in order to adapt the projection effect to the actual posture of the user's head, the real-time pitch angle and roll angle are obtained from the posture sensing system, multiplied by the pitch weighting factor and roll weighting factor respectively, and linearly combined into the posture compensation angle component. This compensation component is used to correct the field of view offset caused by micro-movements of the head to ensure that the projected beam is always locked on the user's gaze area. The vibration compensation angle component, the ambient light adaptation angle component, and the posture compensation angle component are jointly input into the dynamic diffraction angle optimization model. The model sets the reference diffraction angle based on the optical waveguide structure and generates the total dynamic diffraction angle by vector addition. At the same time, to ensure that the angle falls within the effective diffraction bandwidth of the optical waveguide, a constraint is introduced to limit the total angle offset to no more than ±5°. After the angle synthesis is completed, the parameter is modulated with floating-point precision to improve the accuracy to 0.1° level, and finally the dynamic diffraction angle adjustment parameter set is obtained.

[0023] Step 300: Adaptively modulate the electrically controlled liquid crystal layer and the nano-surface grating in the optical waveguide according to the dynamic diffraction angle adjustment parameter set to obtain an optical waveguide coupling efficiency optimization result; Specifically, a voltage-controlled mapping operation is performed on the dynamic diffraction angle adjustment parameter set to convert the abstract angle offset into the voltage drive signal required for physical execution. Based on the set mapping relationship function, the voltage modulation parameters of the liquid crystal layer and the modulation voltage parameters of the nanograting are calculated respectively. In terms of liquid crystal layer control, the electrically controlled liquid crystal layer embedded in the optical waveguide is composed of nematic liquid crystal material. This material has obvious molecular orientation response characteristics under the action of an electric field. Therefore, the corresponding voltage modulation parameters are loaded to the transparent electrodes at both ends of the liquid crystal layer. The liquid crystal molecules are guided to rotate in an orderly manner through the action of a spatially uniform electric field, so that the optical axis direction of the entire liquid crystal layer is dynamically controllable with voltage changes, thereby changing its spatial refractive index distribution, thereby achieving active adjustment of the propagation path and polarization state of the incident light wave, and forming the refractive index distribution adjustment result of the liquid crystal layer. The grating voltage modulation component of the dynamic adjustment parameters is used to control a surface-relief nanograting, a structure etched into the waveguide's exit surface with a period of approximately 380 nm and a depth of 120 nm. By adjusting the effective refractive index difference within the microstructure through an applied voltage, the system achieves precise control of the exit diffraction angle and diffraction efficiency. This modulation not only changes the propagation angle of the exiting beam but also optimizes the light output intensity at different angles, thereby generating a grating diffraction efficiency adjustment result. The results of the liquid crystal layer's refractive index distribution adjustment and the grating's diffraction efficiency adjustment are input into a photodetector to establish a real-time, closed-loop feedback mechanism for the waveguide coupling efficiency. By comparing the measured output optical power data with the target coupling efficiency (e.g., 8.5%), the system determines whether the current modulation has reached the optimal state. If deviation is excessive, the voltage parameters are readjusted for rapid iterative optimization, with an adjustment cycle as short as 10 ms, to consistently maintain the waveguide system within the maximum diffraction efficiency output region.

[0024] Step 400: Based on the optical waveguide coupling efficiency optimization result, the backlight power and display image parameters are coordinated and adjusted, and the smart projection display result is output.

[0025] Specifically, the actual coupling efficiency of the current optical waveguide is compared with the set target coupling efficiency, and a ratio calculation is performed to obtain a power compensation coefficient. This compensation coefficient reflects the additional energy multiplier required to compensate for insufficient coupling efficiency. Real-time ambient light intensity measurements are introduced, and the external lighting conditions are mapped into a visual compensation coefficient using an enhancement function. This coefficient is then multiplied with the power compensation coefficient to obtain the dynamic backlight power. Based on the dynamic backlight power values, a linear brightness response analysis is performed to predict the nonlinear shift in brightness gain caused by power variations. The color temperature drift caused by LED power variations is evaluated, and a set of influencing parameters for brightness linearity and color consistency is established. This set of influencing parameters includes key indicators such as the rate of change in brightness distribution uniformity, the degree of contrast compression, and the range of color saturation drift. This set of influencing parameters is input into the image quality adjustment module, which performs an inverse compensation operation to offset the perceptual distortion caused by physical luminescence variations. In the contrast dimension, a dynamic gamma correction curve is used to inversely enhance contrast loss to maintain image clarity. In the color dimension, a dynamic color saturation gain factor is used to amplify and compensate the RGB channels, thereby offsetting color temperature shifts such as cooler or greener due to power increases. This step results in the coordinated image parameter adjustment values. The dynamic backlight power value and the coordinated image parameter adjustment value are input into the display driver algorithm core, executing a joint optimization process for power and image parameters. During this process, a specific weight fusion strategy is used to balance energy consumption control and visual expression, generating a coordinated adjustment drive parameter group. At the display control execution level, based on this drive parameter group, the image rendering process and LED drive channel are simultaneously controlled in real time. The display quality is continuously monitored through eye tracking sensors and optical feedback modules, and the Q value, a composite quality indicator of current brightness, contrast, and color accuracy, is calculated. When the Q value falls below a set threshold (such as 0.85), a feedback correction mechanism is triggered to recalibrate the adjustment factors to improve image output quality, thereby ensuring stable, clear, and color-consistent smart projection display results under changing environmental conditions.

[0026] In a specific embodiment, the process of executing step 100 may specifically include the following steps: Sampling the data using a three-axis acceleration sensor and a three-axis gyroscope sensor to obtain a raw riding vibration data stream, and performing bandpass filtering and feature extraction on the raw riding vibration data stream to obtain a vibration signal component; The ambient light intensity sensor is used to detect light intensity and extract features to obtain the ambient light intensity component; Integrating the vibration signal component and the ambient light intensity component to obtain a riding environment feature dataset; Performing frequency domain decomposition and harmonic analysis on the vibration signal components in the riding environment characteristic data set to obtain a riding vibration compensation parameter set; A prediction is performed based on the ambient light intensity component in the riding environment feature data set to obtain an ambient light adaptation parameter set.

[0027] Specifically, based on the three-axis acceleration sensor and three-axis gyroscope sensor integrated inside the frame of the smart cycling glasses, linear acceleration and angular velocity data are simultaneously acquired at a high sampling frequency of 1000Hz to form a six-channel raw cycling vibration data stream, which reflects the mechanical disturbance and head micro-movement response experienced by the wearer during cycling. Since the raw data contains low-frequency drift caused by the earth's gravity and high-frequency noise caused by mechanical structure resonance or external equipment, the data stream is band-pass filtered to limit the effective frequency range to 0.5Hz to 50Hz to remove useless signals and retain valuable vibration components. At the same time, the processing results are converted into vibration characteristic indicators that reflect the main frequency characteristics, periodic amplitude, peak position, vibration direction and total energy distribution, forming a structured vibration signal component. On this basis, the system uses the ambient light intensity sensor arranged on the outside of the lens to collect the light intensity of the cycling environment in real time. The sensor's measurement range covers 0.1 lux to 100,000 lux, providing accurate illuminance readings in complex scenarios such as low-light conditions at night, in tunnels, and in direct sunlight. Its response time of less than 10ms ensures sensitive detection of rapid light changes. The collected light intensity data is also low-pass filtered to remove high-frequency light flicker and random jitter. Feature descriptions, including current light intensity, rate of light change, local slope, and gradient of illuminance fluctuation, are extracted to generate an ambient light intensity component. The vibration signal component and the ambient light intensity component are synchronized based on the acquisition time and integrated into a seven-dimensional cycling environment feature dataset consisting of linear acceleration, angular velocity, and light intensity information. This dataset characterizes the user's dynamic environment, including road-induced bumps, head posture changes, and ambient light fluctuations. Frequency domain decomposition and time series feature extraction are performed on the acceleration and angular velocity dimensions in the cycling environment feature dataset to identify the most significant frequency components in the vibration signal and extract representative amplitudes and rhythmic structures to establish a mathematical model of the actual vibration state. The main vibration frequencies generated by riding on different road conditions are concentrated between 1Hz and 20Hz, so the system pays special attention to the energy distribution and rhythm change trends within this frequency band. After feature modeling, a dynamic update mechanism is set up to perform data updates and model corrections every 100ms to ensure that the model can reflect the actual vibration status of the current road conditions in real time. At the same time, a set of vibration level classification standards are introduced to divide the vibration amplitude into three levels: mild (0 to 2m / s 2 ), medium (2 to 5m / s 2 ) and strong (5 to 10 m / s 2), each level corresponds to a set of adjustment weights and compensation response strategies, thereby generating a set of riding vibration compensation parameters covering different intensity conditions. Simultaneously, the system activates a time series prediction module for the ambient light intensity component, using an LSTM architecture based on a deep neural network to learn and model the sequence of light intensity changes over time. This model comprises 64 neural nodes and incorporates a variety of typical lighting scenario samples during training, including direct sunlight on a sunny day, diffuse reflection on a cloudy day, rapid transitions between shaded areas, and transitions into and out of tunnels, enhancing the model's generalization capabilities across multiple scenarios. The final model outputs a predicted value for the future light intensity change trend within a 500ms time window. This allows the system to obtain predicted illuminance values ​​in advance, even before actual ambient light changes have fully occurred, and triggers pre-adjustment operations for the optical system accordingly. The system sets three light intensity response modes: if the predicted light value is less than 1000 lux, the high-gain mode is activated to enhance brightness penetration, and the projection angle is fine-tuned in the negative direction accordingly; if the predicted value is between 1000 lux and 50,000 lux, the standard projection mode is entered to maintain the system default settings; and when the predicted light intensity exceeds 50,000 lux, the anti-glare mode is entered for positive angle adjustment to avoid visual fatigue when the user looks directly at strong light. In addition, if the ambient light intensity change rate exceeds the judgment threshold of 5000 lux / s, the system automatically activates the fast adaptation mechanism and shortens the parameter update cycle from the conventional 200ms to 50ms to ensure the system's timely response to sudden changes in lighting conditions. Through the above steps, the ambient light adaptation parameter set is obtained.

[0028] In a specific embodiment, the step of performing frequency domain decomposition and harmonic analysis on the vibration signal components in the riding environment characteristic dataset to obtain the riding vibration compensation parameter set may specifically include the following steps: Using a Fourier transform algorithm, performing frequency domain conversion on the vibration signal components in the riding environment characteristic dataset to obtain a frequency domain vibration dataset; Extracting harmonic components from the frequency domain vibration data set to obtain a target frequency component data set, and performing third harmonic vibration compensation based on the target frequency component data set to obtain a vibration model parameter set; The three-dimensional optical path offset is calculated according to the vibration model parameter group to obtain a riding vibration compensation parameter set.

[0029] Specifically, the riding environment characteristic dataset consists of three-axis acceleration signals and three-axis gyroscope angular velocity signals. These signals are bandpass filtered to retain the effective vibration components in the 0.5Hz to 50Hz range, forming a set of vibration signal components in the time domain. These signals, acquired continuously at high frequency, record disturbances such as road impact, head deflection, body bounce, and structural resonance experienced during riding. Simply observing these vibration signals in the time domain cannot clearly distinguish their dominant frequency structure, harmonic composition, and spectral distribution characteristics of vibration energy. Therefore, the Fourier transform algorithm is introduced as a key signal conversion method to convert the time series vibration data into a frequency domain representation, constructing a frequency domain vibration dataset. When performing the Fourier transform operation, the system transforms each acceleration and angular velocity channel separately and stores the transformation results in a structured frequency domain matrix. Each frequency point corresponds to the amplitude response of a specific vibration signal at that frequency, thereby intuitively determining the energy distribution of the system in each vibration frequency band. Based on a frequency-domain vibration dataset, harmonic components are extracted from the frequency data, focusing on the energy structure near the fundamental frequency and its second and third harmonics. Peak detection and band energy calculation are used to select a target frequency component data set, which contains the dominant vibration components that the system needs to model and compensate. This data set includes not only the vibration amplitude and phase information corresponding to each target frequency, but also its distribution along three axes and the frequency-domain coupling strength. Third-harmonic vibration compensation is then performed based on the target frequency component data set. This approach uses a third-harmonic combination strategy consisting of the primary, secondary, and tertiary frequencies to establish a vibration compensation model with enhanced fitting accuracy. By incorporating multiple phase, frequency, and amplitude factors, this modeling scheme constructs a vibration response structure with enhanced generalization and real-time adaptability. This approach is capable of approximating the nonlinear vibration behavior caused by complex road conditions, particularly when subjected to the interplay of continuous bumps and irregular disturbances, maintaining a high degree of fit. The system extracts a series of model parameter values ​​from this fitting process, including the dominant amplitudes, phase offsets, and periodic factors of multiple directional components. These values ​​are collectively referred to as the vibration model parameter set. This parameter set is updated every 100ms to adapt to input disturbance fluctuations caused by actual road conditions and changes in user posture. Spatial compensation calculations are performed based on the vibration model parameter set, converting the vibration component in each direction into a spatial displacement consistent with the direction of the optical projection path. These are then combined into a three-dimensional optical path offset expression through directional projection transformation. Considering the optical waveguide system's sensitivity to small angular changes, a high-resolution angle mapping mechanism is constructed so that each vibration directional component, once its amplitude and phase are determined, can be equivalently converted into an offset distance for the optical path in the X, Y, and Z dimensions. This offset distance is further mapped in the optical system into a diffraction angle fine-tuning instruction in the projection direction. This set of three-dimensional optical path offsets is summarized as the riding vibration compensation parameter set.

[0030] In a specific embodiment, the step of performing the prediction based on the ambient light intensity component in the riding environment feature dataset to obtain the ambient light adaptation parameter set may specifically include the following steps: Performing time series processing on the ambient light intensity component in the riding environment feature data set to obtain a light intensity data sequence; Inputting the light intensity data sequence into a long short-term memory network for light intensity prediction to obtain predicted light intensity data, wherein the long short-term memory network includes a first long short-term memory layer, a second long short-term memory layer, and a fully connected layer, wherein the first long short-term memory layer includes 64 long short-term memory units, the second long short-term memory layer includes 128 long short-term memory units, and the fully connected layer uses a ReLU activation function; Optical parameter mapping is performed based on the predicted light intensity data to obtain an optical parameter mapping result, and parameter adaptation is performed according to the optical parameter mapping result and the ambient light intensity change rate to obtain the ambient light adaptation parameter set.

[0031] Specifically, in the cycling environment feature dataset, the ambient light intensity component records the light intensity data during cycling that is continuously monitored by the ambient light intensity sensor on the outside of the glasses using high-frequency sampling. The sensor has a wide measurement range from 0.1 lux to 100,000 lux, and the response time is controlled within 10 milliseconds. It can capture light fluctuations caused by direct sunlight on sunny days, tunnel shadows, tree cover, and vehicle speed. In order to convert the light intensity data into an input format suitable for time series modeling, it is continuously windowed and timestamp aligned to form a light intensity data sequence. The sequence is arranged in chronological order to ensure that the light intensity at different time points has complete before and after context information when modeling. It is also normalized and standardized so that the input data reflects the absolute level and change trend of light on a uniform scale. The light intensity data sequence is input into the long short-term memory network structure for light intensity prediction. The LSTM model architecture consists of two core memory layers and one output mapping structure. The first layer is the basic LSTM layer, containing 64 memory cells. Its primary function is to extract short-term variations in the illumination data sequence, including local fluctuation patterns, periodic trends, and sudden illumination changes, capable of identifying subtle changes in illumination within a few hundred milliseconds. The second layer is the extended LSTM layer, containing 128 memory cells. Building on the first layer's extraction, it captures longer-term, higher-level illumination evolution patterns, thereby building a global perception and structural modeling of future trends. The fully connected layer projects the high-dimensional vector output of the LSTM network into actual illumination predictions. This layer uses the Reluctant Unit (ReLU) activation function to enhance the model's ability to adapt to nonlinear changes and ensure that the output predictions are sensitive to changes in input features at varying illumination rates. With this network architecture, the system generates real-time light intensity predictions for the next 500 milliseconds to 1 second based on the observed light intensity data sequence for the current time period. These predicted light intensity predictions are input into the optical parameter mapping model to construct a response mapping relationship between the ambient light and the optical waveguide system. This mapping strategy is primarily based on the human eye's visual perception characteristics under different light intensities, as well as the sensitivity range of the optical waveguide system's internal coupling efficiency to changes in incident light intensity. This strategy establishes a three-stage response rule. Specifically, when the predicted light intensity is less than 1000 lux, the system enters high-gain mode to enhance brightness perception in low-light environments. Therefore, in this mode, the optical coupling angle is negatively adjusted to increase diffraction intensity. When the predicted value is between 1000 lux and 50,000 lux, the system maintains standard mode, with the default angle setting unchanged, to balance energy consumption and display brightness. When the predicted light intensity exceeds 50,000 lux, the system enters anti-glare mode, using a positive angle shift to reduce the direct impact of excessive light on the eyes, improving image readability and comfort.This three-stage mapping model ensures comfortable and stable adjustment of the optical system in various environments. Using a built-in optical path coupling geometry model, the predicted light intensity is mapped into optical angle response or gain parameters, forming a preliminary optical parameter mapping result. To improve the accuracy and adaptability of the response, the system incorporates real-time detection of the current illumination change rate. This dynamic factor, along with the optical parameter mapping result, serves as the basis for parameter adaptation. During actual system operation, when the illumination change rate dL / dt exceeds the set threshold of 5000 lux / s, the system identifies the current environment as experiencing rapid changes, such as in tunnels, interlaced tree shadows, or sunlight obstructed by clouds. At this point, the system immediately switches to fast-response mode, activating the high-priority adjustment channel and shortening the parameter adaptation window from the default 200 milliseconds to less than 50 milliseconds. This allows the system to complete the corresponding optical system angle compensation and gain correction before the sudden illumination change degrades image readability. Ultimately, the system, driven by both the predicted results and the change rate factor, achieves multi-parameter joint adaptation, generating a set of ambient light adaptation parameters.

[0032] In a specific embodiment, the process of executing step 200 may specifically include the following steps: Performing a weighted calculation of frequency domain components based on the riding vibration compensation parameter set to obtain a vibration compensation angle component; Perform optical parameter mapping calculation according to the ambient light adaptation parameter set to obtain an ambient light adaptation angle component; Combined with riding posture data, the head pitch angle and roll angle of the smart riding glasses are weightedly fused to obtain the posture compensation angle component; The vibration compensation angle component, the ambient light adaptation angle component, and the posture compensation angle component are optically waveguide coupled to obtain a dynamic diffraction angle adjustment parameter set.

[0033] Specifically, the system uses a riding vibration compensation parameter set that includes mathematical modeling results for disturbances such as bumps, vibrations, body bounce, and micro-vibrations that occur during riding. These modeling results, after high-order harmonic decomposition and parameter fitting, record the main amplitude distribution, frequency-domain energy concentration, phase characteristics, and directional response ratio within typical frequency bands. Based on this, the system weights different components within the frequency domain. The dominant frequency band is given a higher weight because it contributes most significantly to optical path deviation, while high-frequency or non-dominant frequencies are assigned lower weights, effectively suppressing the destabilizing effects of atypical vibrations on the system. Through a frequency-domain component weighting mechanism, the vibration responses corresponding to multiple frequency components are projected and superimposed in spatial directions to form a single optical offset, the vibration compensation angle component. This component represents the correction angle applied to the diffraction direction of the optical waveguide due to vibration in three-dimensional space, used to correct for projection offsets caused by changes in the optical path direction. Based on parameters such as the predicted light intensity and illumination change rate output by the ambient light adaptation parameter set, the optical mapping model is activated and the corresponding diffraction angle adjustment strategy is calculated. Because the human eye's sensitivity to brightness, contrast, and image clarity varies significantly under different illumination conditions, the system categorizes the mode into high-gain, standard, and anti-glare modes based on the predicted illumination level. In low-light conditions, a negative angle offset increases the incident energy density to boost image brightness. In medium light, the system maintains the original angle setting for stability. In strong light, a positive angle offset reduces the output brightness to prevent glare. Therefore, after receiving the ambient light adaptation parameters, the system uses mapping logic to calculate the most appropriate output angle response setting for the current ambient light conditions. It then generates an ambient light adaptation angle component, which reflects the amount of optical deflection required to maintain eye comfort and image legibility under the current light level. Furthermore, to enhance the system's adaptability to the wearer's dynamic head posture, the system uses a three-axis gyroscope and accelerometer mounted inside the frame to generate riding posture data in real time. This data records fluctuations in the user's head pitch and roll angles during riding due to head turning, upward and downward gaze adjustments, and road impact. The system assigns weighted coefficients to the pitch and roll angles, with the pitch angle having a greater impact on the vertical direction of the projection path and therefore receiving a higher weight. The roll angle, which primarily contributes to horizontal deviation, receives a relatively lower weight. These two components are linearly weighted and combined to form a posture compensation angle component, representing the compensation for changes in projection direction caused by the tilt of the user's head relative to the reference plane. The vibration compensation angle component, the ambient light adaptation angle component, and the posture compensation angle component are optically coupled to construct a dynamic diffraction angle adjustment parameter set. During the fusion process, a constraint mechanism is introduced to ensure that the resulting angle superposition remains within the optical waveguide operating range. This means that the final composite angle deviation does not exceed a safe range of ±5 degrees from the set reference angle to prevent total reflection failure in the optical waveguide or projection deviation from the effective field of view.At the same time, after the synthetic angle calculation is completed, the result accuracy is optimized to 0.1 degree level to meet the high-precision requirements of the micro-optical diffraction structure for angle input and maintain display stability and visual consistency.

[0034] In a specific embodiment, the step of performing optical waveguide coupling on the vibration compensation angle component, the ambient light adaptation angle component, and the posture compensation angle component to obtain a dynamic diffraction angle adjustment parameter set may specifically include the following steps: Performing optical waveguide geometric factor correction on the vibration compensation angle component to obtain a vibration angle parameter after geometric correction; Reconstructing the sinusoidal wave of the frequency domain component based on the vibration angle parameter after the geometric correction to obtain a reconstructed vibration compensation angle value; performing differential weighted calculation of the pitch angle and the roll angle based on the attitude compensation angle component to obtain a weighted attitude compensation angle value; A weighted coefficient matrix is ​​established according to the reconstructed vibration compensation angle value, the ambient light adaptation angle component and the weighted posture compensation angle value, and a linear combination is performed based on the weighted coefficient matrix to obtain a dynamic diffraction angle adjustment parameter set.

[0035] Specifically, the optical waveguide geometry factor correction operation is performed based on the vibration compensation angle component. The angular response is adjusted according to the geometric parameters of the optical waveguide body. This involves multiple spatially constrained variables, including the optical path length, the coupling incident angle, the number of reflective layers in the waveguide, and the position of the exit surface. The correction goal is to project the vibration angle compensation value onto the actual impact scale of the output direction deviation in the actual optical path, thereby obtaining the geometrically corrected vibration angle parameters. Based on the geometrically corrected vibration angle parameters, a sinusoidal wave reconstruction of the frequency domain components is performed. The main frequency, second harmonic, and third harmonic components in the vibration spectrum are synthesized according to their amplitude and phase weights, and the equivalent vibration angle variation trend is restored on the time axis, resulting in a continuous, controllable, and well-fitting reconstructed vibration compensation angle value. Simultaneously, the attitude compensation angle component is optimized. Because the original attitude angle component consists of two independent measurements, the pitch angle and the roll angle, which are inconsistent in terms of directional coupling and amplitude superposition in the spatial coordinate system, the system introduces a differential weighting mechanism to perform combined optimization. During this process, the system performs differential calculations based on the pitch and roll angle rates at each moment, extracting their dynamic weight distributions over time. These are then weighted and fused with a preset directional weighting factor to obtain a weighted attitude compensation angle value. By introducing differential components and temporal dynamic response factors, weighted attitude compensation can more effectively track the rhythm of the wearer's head's changing perspective over time, extending the compensation mechanism beyond static attitude shifts to a more dynamic response. A weighting coefficient matrix is ​​established based on the reconstructed vibration compensation angle value, the ambient light adaptation angle component, and the weighted attitude compensation angle value. Weights in this matrix are assigned based on the sensitivity of the disturbance source to visual shifts. The vibration factor has the greatest influence, particularly on uneven roads or high-speed riding scenarios, and its corresponding weight is therefore set as the dominant term. The attitude compensation factor is dynamically adjusted based on the wearer's behavioral characteristics, with its weight fluctuating based on the pitch rate and roll amplitude. The ambient light adaptation angle component is weighted more heavily in bright or low light environments and less heavily in moderate illumination, thus achieving adaptive weighting modeling of multi-dimensional disturbance factors. After the weighted coefficient matrix is ​​constructed, the three groups of angle components are multiplied by their corresponding weights through linear combination and summed up to obtain the fused dynamic diffraction angle adjustment parameter set.

[0036] In a specific embodiment, the process of executing step 300 may specifically include the following steps: Performing voltage control mapping based on the dynamic diffraction angle adjustment parameter set to obtain liquid crystal layer voltage modulation parameters and grating voltage modulation parameters; performing electric field modulation on the electrically controlled liquid crystal layer to orient nematic liquid crystal molecules according to the liquid crystal layer voltage modulation parameter, thereby obtaining a result of adjusting the refractive index distribution of the liquid crystal layer; Dynamically adjusting the effective refractive index difference of the nano-surface grating based on the grating voltage modulation parameter to obtain a grating diffraction efficiency adjustment result; The adjustment result of the refractive index distribution of the liquid crystal layer and the adjustment result of the grating diffraction efficiency are input into a photodetector to monitor the light intensity, and the optimization result of the optical waveguide coupling efficiency is obtained.

[0037] Specifically, based on a set of dynamic diffraction angle adjustment parameters, a preset voltage-controlled mapping model is invoked. This model establishes an angle-to-voltage conversion function based on the physical properties of the electric field responses of different material layers within the optical waveguide structure, dielectric thickness, the dielectric anisotropy of the liquid crystal molecules, and the refractive index adjustment range of the grating structure. This function maps any set of diffraction angle changes into the voltage values ​​required for the liquid crystal layer and the grating modulation structure, thereby outputting the liquid crystal layer voltage modulation parameters and the grating voltage modulation parameters, respectively. Taking into account the high sensitivity of optical waveguide systems to angular variations, the system incorporates a piecewise linear fitting strategy into the mapping function to ensure sufficient control accuracy and response resolution for the voltage outputs corresponding to different angular variation ranges. The liquid crystal layer voltage modulation parameters are input into the drive channel of the electrically controlled liquid crystal layer. The liquid crystal layer is composed of a nematic liquid crystal material with a thickness of approximately 15 microns. Its physical properties exhibit highly ordered molecular steering behavior under the action of an electric field. Specifically, by controlling the voltage applied between the electrodes at the two ends of the liquid crystal layer, the system can continuously change the alignment of the liquid crystal molecules, thereby dynamically varying the effective refractive index in different spatial directions. Because changes in the optical axis orientation of liquid crystal molecules directly affect the phase delay and refractive path of a light beam traveling through the waveguide, electric field modulation is used to precisely control the deflection of the projected optical path. Driven by voltage modulation parameters, molecules within the liquid crystal layer reorient themselves, creating a gradient-varying refractive index distribution. This results in a controllable wavefront modulation effect as the light beam passes through the liquid crystal layer. This modulation results in a controlled adjustment of the liquid crystal layer's refractive index distribution, which manifests itself spatially as a combined output of optical path offset, beam shaping, and focus fine-tuning capabilities. Simultaneously, a nanostructured relief grating on the waveguide surface is controlled in parallel with the liquid crystal layer. This grating has a designed period of approximately 380 nanometers and a depth of approximately 120 nanometers. Its core function is to redistribute the light beam's exit angle and diffraction efficiency at the output end, improving overall coupling efficiency and enabling energy redirection between different diffraction states. In terms of control logic, the system inputs the grating voltage modulation parameters into the control channel on the nano-grating surface. This channel embeds a controllable dielectric or piezoelectric material under the nanostructure, which induces a local stress field or micro-scale deformation under the action of voltage changes, thereby changing the equivalent refractive index distribution difference around the grating structure, thereby affecting the Bragg diffraction conditions in this area and completing high-efficiency diffraction operations on light beams at different angles. The voltage modulation amplitude determines the achievable range of refractive index difference changes, and thus determines the adjustable diffraction efficiency range. Under this effect, the grating structure can adjust its optimal diffraction angle direction according to dynamic angle instructions, so that the optical waveguide system can maintain a high-coupling energy conversion path under different user viewing angles, vibration states or lighting environments, avoiding the performance degradation of the traditional fixed grating structure that experiences a sudden drop in diffraction efficiency under large-angle offset conditions.This dynamic process generates the grating diffraction efficiency adjustment result, recording the current diffraction energy utilization and diffraction distribution status of the grating in the target direction. In order to monitor the execution effect of the optical waveguide adjustment system in real time, the system embeds a high-precision photodetector at the end of the optical waveguide output channel to monitor the current actual light intensity and serve as a feedback signal source for coupling efficiency evaluation. During the execution process, the liquid crystal layer refractive index distribution adjustment result and the grating diffraction efficiency adjustment result will be synchronously input into the calculation path of the detector. The detector performs light intensity integration and directionality analysis on the output light to determine whether the current output flux meets the coupling target. The system compares the measured light intensity with the preset target coupling efficiency threshold. If the light flux is low or the energy distribution deviates significantly, the control module triggers the feedback mechanism to adjust the parameter slope or bias value in the voltage control mapping relationship to improve the modulation accuracy of the next cycle. The feedback cycle is set to less than 10 milliseconds, which can achieve a closed-loop update frequency of hundreds of times per second at normal riding speeds. This ensures that when the user continues to move or road vibrations change drastically, the optical waveguide system still maintains stable coupling output and visual consistency, forming a fast-response, high-precision, and highly stable light field modulation closed loop.

[0038] In a specific embodiment, the step of performing voltage control mapping based on the dynamic diffraction angle adjustment parameter set to obtain the liquid crystal layer voltage modulation parameters and the grating voltage modulation parameters may specifically include the following steps: Calculating the reference angle difference and angle change rate of the dynamic diffraction angle adjustment parameter set to obtain an angle offset and angle change speed parameter set; Performing liquid crystal molecule orientation angle mapping based on the angle offset to obtain a target liquid crystal orientation angle value, and performing electric field intensity conversion according to the target liquid crystal orientation angle value to obtain a liquid crystal layer voltage modulation parameter; Grating effective refractive index difference mapping is performed according to the angle offset and the angle change speed parameter group to obtain a target refractive index difference value, and surface relief grating voltage conversion is performed based on the target refractive index difference value to obtain a grating voltage modulation parameter.

[0039] Specifically, a baseline angle difference calculation is performed on the dynamic diffraction angle adjustment parameter set, using the preset optical waveguide baseline diffraction angle as a reference angle. This baseline angle is preset to 15 degrees. The current dynamic angle is then subtracted from this baseline angle to obtain an angle offset. This angle offset is used to characterize the total degree of deflection of the current system in response to riding environment disturbances. Simultaneously, a time difference calculation is performed on the angle parameter set to analyze the amplitude of change per unit time, i.e., the angle change rate. This generates an angle change rate parameter set, which reflects the dynamic response characteristics of the angle change trend and is used to predict the direction and speed of upcoming angle changes. After obtaining the angle offset, the system performs response modeling of the liquid crystal control path. In the liquid crystal layer control logic, the orientation angle of the liquid crystal molecules directly determines their local refractive index distribution. The liquid crystal orientation angle is, in turn, constrained by the direction and intensity of the electric field applied across it. Therefore, a mapping relationship is established between the angle offset and the liquid crystal molecular orientation angle. The system establishes an orientation angle mapping model based on the material response characteristics and geometric boundary conditions of the liquid crystal layer. This model stipulates that when the angle offset is within ±0.1 degrees, the original orientation state is maintained. However, when the offset exceeds 0.1 degrees, the target orientation angle is converted linearly into a desired orientation angle change, taking into account the spatial distribution of the liquid crystal layer thickness and polarization direction, and outputting a target liquid crystal orientation angle. This angle value is then input into the electric field intensity conversion module, which converts the target orientation angle into the corresponding electric field intensity demand based on the dielectric anisotropy parameters and response function of the nematic liquid crystal molecules. The system then converts the electric field intensity into the required liquid crystal layer voltage modulation parameter based on the capacitance structure and spatial distribution of the liquid crystal layer material. This parameter is the electrical signal input required to drive the liquid crystal molecules to reorient, expressed in volts and controlled between 0V and 10V. The system sets the voltage ramp-up and ramp-down slope based on the rate of change to prevent excessive molecular oscillation or response lag. Simultaneously, in the grating control path, the system generates the relief grating voltage drive parameters based on two input factors: the angle offset and the angle change rate parameter set. Based on the angular offset, the system activates the grating effective refractive index difference mapping model. This model defines the grating refractive index difference required for different angular offsets, thereby ensuring maximum diffraction efficiency at a given diffraction angle. Because the diffraction behavior of the grating structure is not only related to the angle itself but also to its changing trend, the system introduces an angle change rate parameter as an adjustment factor to dynamically correct the target refractive index difference. When the angle changes rapidly, the refractive index adjustment amplitude is increased to cope with rapid system deflection. When the angle change tends to be stable, the output is maintained to ensure image consistency. Through this step, the target refractive index difference value is obtained.The surface relief grating voltage is converted based on the target refractive index difference value. According to the piezoelectric response material characteristics in the grating surface structure, a voltage conversion model is established. This model takes into account the coupling relationship between the grating structure period, groove depth, incident angle cosine factor and the refractive index of the reflective layer medium, and converts the target refractive index difference value into a control voltage for activating the micro-deformation of the relief grating, thereby forming a grating voltage modulation parameter. In actual control, this parameter is controlled within a dynamic range of several volts to more than ten volts. The system dynamically adjusts the rising edge and steady-state holding time according to the change rate to ensure that the grating diffraction state always fits the target angle compensation path.

[0040] In a specific embodiment, the process of executing step 400 may specifically include the following steps: Calculating a ratio of a target coupling efficiency to a current coupling efficiency based on the optical waveguide coupling efficiency optimization result to obtain a power compensation coefficient, and calculating a backlight power gain based on the power compensation coefficient and ambient light intensity to obtain a dynamic backlight power value; Performing brightness linearity analysis and color temperature offset prediction on the dynamic backlight power value to obtain a parameter group of the impact of power change on image display, and performing image contrast inverse compensation and color saturation inverse compensation based on the influencing parameter group to obtain a collaborative image parameter adjustment value; Inputting the dynamic backlight power value and the collaborative image parameter adjustment value into a display driving algorithm to perform power and image joint optimization to obtain a collaboratively adjusted driving parameter group; Real-time display quality monitoring and dynamic feedback correction are performed based on the collaboratively adjusted driving parameter group, and the intelligent projection display result is output.

[0041] Specifically, the actual coupling efficiency reported by the optical system is compared with the system's preset target coupling efficiency, which serves as the basis for adjusting backlight power and image rendering parameters. The system's target coupling efficiency, set at 8.5%, represents the maximum energy utilization achievable under an ideal structure and optimized optical path. The current coupling efficiency is measured in real time by a photodetector during actual operation. This measurement is influenced by a variety of factors, including the liquid crystal layer's orientation response, the diffraction state of the nanograting, variations in the light's incident angle, and micro-vibration interference, resulting in dynamic fluctuations. The current coupling efficiency is then compared to the target value to generate a power compensation coefficient, representing the additional energy required to offset the decrease in coupling efficiency. When the compensation coefficient is less than 1, the optical waveguide is performing well and the current power output is maintained. When the coefficient is greater than 1, the backlight system's luminous power needs to be increased to ensure the final output luminous flux falls within the human eye's perceptible brightness range. To ensure that power regulation more closely matches actual lighting conditions, a dynamic factor, ambient light intensity, is incorporated into the compensation coefficient. This factor uses the ambient light intensity value collected by an external ambient light sensor in real time and weighted by a built-in light perception function. The system calculates a dynamic backlight power value based on the product of the power compensation coefficient and the illumination compensation function. This value physically controls the actual driving current of the LED backlight unit, with a control range of 200mW to 400mW. In bright sunlight, the system actively increases backlight power to enhance image brightness, while in dim scenes, it actively reduces power consumption to prevent glare or excessive power consumption. The system analyzes the dynamic backlight power value to predict its potential impact on the displayed image. In the luminance dimension, a luminance linearity analysis is performed to determine whether the response curve of LED power changes to light output conforms to a linear law. If nonlinear response or interval jumps are detected, the system reserves compensation coefficients to prepare for contrast correction. In the color dimension, the system models the LED spectral drift caused by current changes and performs color temperature offset prediction. By fitting historical data with the current temperature, voltage, and current conditions, the direction and magnitude of color temperature offset are inferred. This parameter set is used to construct a parameter set that reflects the impact of power changes on image display. This parameter set includes information such as the luminance offset, contrast compression trend, and the color saturation tilt ratio of the red, green, and blue channels. Image contrast and color saturation are reversely compensated based on the influencing parameter group. In terms of contrast, a dynamic reverse enhancement mechanism is used to perform reverse gain processing on the image signal based on the results of nonlinear brightness analysis. This improves the response sensitivity of low-grayscale areas of the image and prevents whitening of highlight areas or loss of dark details after brightness is increased. In terms of color saturation, reverse color correction is performed on the three color channels based on the color temperature offset direction. If the system predicts blue light enhancement, the red and green channel contrast weights are increased. If the system predicts green light enhancement, the oversaturated green flux is suppressed, thereby constructing a collaborative image parameter adjustment value with realistic visual restoration capabilities.The two control parameters are simultaneously input into the display driver algorithm, executing a joint optimization process. Within this process, a multi-objective weighted function is employed to optimize power control and image adjustment, maintaining a balance between image brightness stability, color reproduction, visual comfort, and power efficiency. The algorithm uses learning rules to identify when to prioritize power for high-brightness mode enhancement and when to prioritize image quality for fine-tuning mode. It then outputs a coordinated set of driver parameters, including backlight power control commands, RGB image signal correction vectors, and gamma curve calibration parameters. These parameters are then directly applied to the image rendering processing chip and the backlight driver control module, achieving synchronized adjustments at both the image and energy levels. To ensure continuous and stable operation of the entire process in dynamic environments, the system utilizes a display quality monitoring and feedback mechanism for real-time evaluation of the final image output status. The system uses eye tracking, light intensity measurement, image consistency evaluation and other means to construct multi-dimensional display quality indicators such as brightness uniformity, contrast retention, and color accuracy, and combines them into a unified quality assessment function Q value. If the system detects that the Q value is lower than the set threshold (such as 0.85), it immediately returns the current state parameters, triggering the next round of compensation calculation and drive parameter reconstruction, to achieve a continuous and adaptive closed-loop optimization process.

[0042] The above describes the information projection method of the smart cycling glasses in the embodiment of the present invention. The following describes the information projection device of the smart cycling glasses in the embodiment of the present invention. Figure 2 An embodiment of the information projection device of the smart cycling glasses in the embodiment of the present invention includes: An acquisition module 21 is configured to acquire a riding environment feature data set during riding, and generate a riding vibration compensation parameter set and an ambient light adaptation parameter set based on the riding environment feature data set; an optical waveguide coupling module 22, configured to perform optical waveguide coupling on the smart cycling glasses according to the cycling vibration compensation parameter set and the ambient light adaptation parameter set, to obtain a dynamic diffraction angle adjustment parameter set; An adaptive modulation module 23 is configured to adaptively modulate the electrically controlled liquid crystal layer and the nano-surface grating in the optical waveguide according to the dynamic diffraction angle adjustment parameter set to obtain an optical waveguide coupling efficiency optimization result; The collaborative adjustment module 24 is used to collaboratively adjust the backlight power and display image parameters based on the optical waveguide coupling efficiency optimization result, and output the intelligent projection display result. Through the collaborative efforts of these components, a comprehensive riding environment perception system is established by integrating a triaxial accelerometer, a triaxial gyroscope, and an ambient light intensity sensor. Compared to existing single-sensor solutions, this system can simultaneously capture multi-dimensional environmental characteristics including vibration, posture, and illumination. Using a Fourier transform algorithm and a third-harmonic vibration compensation model, it accurately analyzes the frequency domain characteristics of riding vibration and applies targeted compensation. Compared to traditional time-domain linear compensation methods, this significantly suppresses the interference of vibration on the optical path, ensuring the stability of the displayed image. A two-layer LSTM network architecture is used to predict ambient light intensity. Compared to the passive light intensity adaptation method of the existing technology, this architecture achieves active prediction and preemptive adjustment, effectively resolving the display lag caused by rapid changes in ambient light and improving the environmental adaptability of the display system. A three-dimensional coupled optimization algorithm for vibration compensation, ambient light adaptation, and riding posture is developed. Using a linear combination of weighted coefficient matrices, this achieves multi-factor coordinated optimization, significantly improving the coupling efficiency of the optical waveguide compared to the single parameter adjustment of the existing technology. Through electric field modulation of nematic liquid crystal molecular orientation and dynamic adjustment of the effective refractive index difference of nano-surface grating, real-time adjustment of the optical properties of the optical waveguide is achieved compared to the traditional fixed optical structure, and a power-image joint optimization mechanism is established. Through brightness linearity analysis and reverse compensation algorithm, compared with the independent parameter adjustment method of the existing technology, the coordinated optimization of backlight power and image parameters is achieved, ensuring the consistency and stability of display quality.

[0043] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling an electronic device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0044] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for projecting information on smart cycling glasses, characterized in that: include: Collecting a riding environment feature data set during riding, and generating a riding vibration compensation parameter set and an ambient light adaptation parameter set according to the riding environment feature data set; Performing optical waveguide coupling on the smart cycling glasses according to the cycling vibration compensation parameter set and the ambient light adaptation parameter set to obtain a dynamic diffraction angle adjustment parameter set; Adaptively modulating the electrically controlled liquid crystal layer and the nano-surface grating in the optical waveguide according to the dynamic diffraction angle adjustment parameter set to obtain an optical waveguide coupling efficiency optimization result; Based on the optical waveguide coupling efficiency optimization result, the backlight power and display image parameters are coordinated to output the intelligent projection display result.

2. The information projection method of the smart cycling glasses according to claim 1, characterized in that: The collecting of a riding environment feature data set during riding, and generating a riding vibration compensation parameter set and an ambient light adaptation parameter set according to the riding environment feature data set, includes: Sampling the data using a three-axis acceleration sensor and a three-axis gyroscope sensor to obtain a raw riding vibration data stream, and performing bandpass filtering and feature extraction on the raw riding vibration data stream to obtain a vibration signal component; The ambient light intensity sensor is used to detect light intensity and extract features to obtain the ambient light intensity component; Integrating the vibration signal component and the ambient light intensity component to obtain a riding environment feature dataset; Performing frequency domain decomposition and harmonic analysis on the vibration signal components in the riding environment characteristic data set to obtain a riding vibration compensation parameter set; A prediction is performed based on the ambient light intensity component in the riding environment feature data set to obtain an ambient light adaptation parameter set.

3. The information projection method of the smart cycling glasses according to claim 2, characterized in that: The performing frequency domain decomposition and harmonic analysis on the vibration signal components in the riding environment characteristic data set to obtain a riding vibration compensation parameter set includes: Using a Fourier transform algorithm, performing frequency domain conversion on the vibration signal components in the riding environment characteristic dataset to obtain a frequency domain vibration dataset; Extracting harmonic components from the frequency domain vibration data set to obtain a target frequency component data set, and performing third harmonic vibration compensation based on the target frequency component data set to obtain a vibration model parameter set; The three-dimensional optical path offset is calculated according to the vibration model parameter group to obtain a riding vibration compensation parameter set.

4. The information projection method of the smart cycling glasses according to claim 2, characterized in that: The step of predicting the ambient light intensity component in the riding environment feature dataset to obtain an ambient light adaptation parameter set includes: Performing time series processing on the ambient light intensity component in the riding environment feature data set to obtain a light intensity data sequence; Inputting the light intensity data sequence into a long short-term memory network for light intensity prediction to obtain predicted light intensity data, wherein the long short-term memory network includes a first long short-term memory layer, a second long short-term memory layer, and a fully connected layer, wherein the first long short-term memory layer includes 64 long short-term memory units, the second long short-term memory layer includes 128 long short-term memory units, and the fully connected layer uses a ReLU activation function; Optical parameter mapping is performed based on the predicted light intensity data to obtain an optical parameter mapping result, and parameter adaptation is performed according to the optical parameter mapping result and the ambient light intensity change rate to obtain the ambient light adaptation parameter set.

5. The information projection method of the smart cycling glasses according to claim 1, characterized in that: The step of performing optical waveguide coupling on the smart cycling glasses according to the cycling vibration compensation parameter set and the ambient light adaptation parameter set to obtain a dynamic diffraction angle adjustment parameter set includes: Performing a weighted calculation of frequency domain components based on the riding vibration compensation parameter set to obtain a vibration compensation angle component; Perform optical parameter mapping calculation according to the ambient light adaptation parameter set to obtain an ambient light adaptation angle component; Combined with riding posture data, the head pitch angle and roll angle of the smart riding glasses are weightedly fused to obtain the posture compensation angle component; The vibration compensation angle component, the ambient light adaptation angle component, and the posture compensation angle component are optically waveguide coupled to obtain a dynamic diffraction angle adjustment parameter set.

6. The information projection method of the smart cycling glasses according to claim 5, characterized in that: The performing optical waveguide coupling on the vibration compensation angle component, the ambient light adaptation angle component, and the posture compensation angle component to obtain a dynamic diffraction angle adjustment parameter set includes: Performing optical waveguide geometric factor correction on the vibration compensation angle component to obtain a vibration angle parameter after geometric correction; Reconstructing the sinusoidal wave of the frequency domain component based on the vibration angle parameter after the geometric correction to obtain a reconstructed vibration compensation angle value; performing differential weighted calculation of the pitch angle and the roll angle based on the attitude compensation angle component to obtain a weighted attitude compensation angle value; A weighted coefficient matrix is ​​established according to the reconstructed vibration compensation angle value, the ambient light adaptation angle component and the weighted posture compensation angle value, and a linear combination is performed based on the weighted coefficient matrix to obtain a dynamic diffraction angle adjustment parameter set.

7. The information projection method of the smart cycling glasses according to claim 1, characterized in that: Adaptively modulating the electrically controlled liquid crystal layer and the nano-surface grating in the optical waveguide according to the dynamic diffraction angle adjustment parameter set to obtain an optical waveguide coupling efficiency optimization result includes: Performing voltage control mapping based on the dynamic diffraction angle adjustment parameter set to obtain liquid crystal layer voltage modulation parameters and grating voltage modulation parameters; performing electric field modulation on the electrically controlled liquid crystal layer to orient nematic liquid crystal molecules according to the liquid crystal layer voltage modulation parameter, thereby obtaining a result of adjusting the refractive index distribution of the liquid crystal layer; Dynamically adjusting the effective refractive index difference of the nano-surface grating based on the grating voltage modulation parameter to obtain a grating diffraction efficiency adjustment result; The adjustment result of the refractive index distribution of the liquid crystal layer and the adjustment result of the grating diffraction efficiency are input into a photodetector to monitor the light intensity, and the optimization result of the optical waveguide coupling efficiency is obtained.

8. The information projection method of the smart cycling glasses according to claim 7, characterized in that: The performing voltage control mapping based on the dynamic diffraction angle adjustment parameter set to obtain liquid crystal layer voltage modulation parameters and grating voltage modulation parameters includes: Calculating the reference angle difference and angle change rate of the dynamic diffraction angle adjustment parameter set to obtain an angle offset and angle change speed parameter set; Performing liquid crystal molecule orientation angle mapping based on the angle offset to obtain a target liquid crystal orientation angle value, and performing electric field intensity conversion according to the target liquid crystal orientation angle value to obtain a liquid crystal layer voltage modulation parameter; Grating effective refractive index difference mapping is performed according to the angle offset and the angle change speed parameter group to obtain a target refractive index difference value, and surface relief grating voltage conversion is performed based on the target refractive index difference value to obtain a grating voltage modulation parameter.

9. The information projection method of the smart cycling glasses according to claim 1, characterized in that: The backlight power and display image parameters are coordinated adjusted based on the optical waveguide coupling efficiency optimization result, and the smart projection display result is output, including: Calculating a ratio of a target coupling efficiency to a current coupling efficiency based on the optical waveguide coupling efficiency optimization result to obtain a power compensation coefficient, and calculating a backlight power gain based on the power compensation coefficient and ambient light intensity to obtain a dynamic backlight power value; Performing brightness linearity analysis and color temperature offset prediction on the dynamic backlight power value to obtain a parameter group of the impact of power change on image display, and performing image contrast inverse compensation and color saturation inverse compensation based on the influencing parameter group to obtain a collaborative image parameter adjustment value; Inputting the dynamic backlight power value and the collaborative image parameter adjustment value into a display driving algorithm to perform power and image joint optimization to obtain a collaboratively adjusted driving parameter group; Real-time display quality monitoring and dynamic feedback correction are performed based on the collaboratively adjusted driving parameter group, and the intelligent projection display result is output.

10. An information projection device for smart cycling glasses, characterized in that: The method for executing information projection of the smart cycling glasses according to any one of claims 1 to 9 comprises: An acquisition module is used to collect a riding environment feature data set during riding, and generate a riding vibration compensation parameter set and an ambient light adaptation parameter set according to the riding environment feature data set; an optical waveguide coupling module, configured to perform optical waveguide coupling on the smart cycling glasses according to the cycling vibration compensation parameter set and the ambient light adaptation parameter set, to obtain a dynamic diffraction angle adjustment parameter set; An adaptive modulation module, configured to adaptively modulate the electrically controlled liquid crystal layer and the nano-surface grating in the optical waveguide according to the dynamic diffraction angle adjustment parameter set, to obtain an optical waveguide coupling efficiency optimization result; A collaborative adjustment module is used to collaboratively adjust the backlight power and display image parameters based on the optical waveguide coupling efficiency optimization result, and output the intelligent projection display result.

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